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* feat: adopt directory-based docs versioning with Edge channel Switch docs.crewai.com from navigation-only versioning (every version selector entry rendered the same docs/<lang>/* source files) to Mintlify's directory-based versioning so each version selector entry renders its own snapshot. Add an "Edge" channel under docs/edge/<lang>/* that always reflects main HEAD for unreleased work, eliminating pre-release leakage onto frozen release labels. External links to canonical /<lang>/* URLs are preserved via wildcard redirects that always land on the current default version. Layout: - docs/edge/<lang>/* rolling source (you edit here) - docs/edge/enterprise-api.*.yaml - docs/v<X.Y.Z>/<lang>/* frozen, immutable snapshots - docs/v<X.Y.Z>/enterprise-api.*.yaml - docs/images/ shared, append-only - docs/docs.json nav + redirects URLs follow the Mintlify-idiomatic shape: /edge/<lang>/<page> for Edge, /v<X.Y.Z>/<lang>/<page> for every frozen snapshot. The wildcard redirects /<lang>/:slug* -> /<default>/<lang>/:slug* keep stale links working, and every freeze rewrites them (plus all per-section/per-page redirects) so destinations always resolve to the current default without depending on a second redirect hop. Release flow integration (devtools release): - New module crewai_devtools.docs_versioning.freeze() materialises docs/v<X.Y.Z>/ from docs/edge/, rewrites openapi: refs inside the snapshot, inserts the version into every language block in docs.json, and refreshes all redirect destinations. - _update_docs_and_create_pr() in cli.py now calls that freeze during Phase 2 of devtools release. Edge changelogs are updated first (so the snapshot freeze picks them up), then the snapshot is staged alongside docs.json, branched as docs/freeze-v<X.Y.Z>, and the PR is titled [docs-freeze] docs: snapshot and changelog for v<X.Y.Z> — the title prefix the new CI guard reads. - The PR still gates tag, GitHub release, PyPI publish, and the enterprise release as before; no new PRs are added. - Pre-releases (1.X.YaN, 1.X.YbN, ...) skip the snapshot — they ride Edge — and the docs PR title omits the [docs-freeze] prefix. - docs_check (AI-generated docs scaffolding) writes to docs/edge/<lang>/* so newly-generated unreleased docs land in Edge and never accidentally touch a frozen snapshot. Migration scripts (one-shot): - scripts/docs/freeze_historical_versions.py reconstructs all 16 historical snapshots (v1.10.0 .. v1.14.7) from git tags via git archive | tar, rewriting openapi: MDX refs so each snapshot reads its own enterprise-api YAML rather than the live one. - scripts/docs/prefix_version_paths.py one-shot-migrates docs.json: rewrites every page path in 16 versioned blocks to point under docs/v<X.Y.Z>/, inserts a new Edge entry per language, tags v1.14.7 as Latest (default), prunes pages whose target file doesn't exist in the snapshot (e.g. docs/ar/ didn't exist before v1.12.0), and writes the wildcard + per-section redirects. - scripts/docs/freeze_current_edge.py is now a thin CLI wrapper around docs_versioning.freeze for manual one-off freezes (e.g. retroactively snapshotting a forgotten release). CI guards (.github/workflows/docs-snapshots.yml): - Frozen snapshots under docs/v[0-9]*/ are immutable; only PRs whose title contains [docs-freeze] (i.e. release-cut PRs generated by devtools release or the manual wrapper) may modify them. - Images under docs/images/ are append-only since snapshots share a single image directory. Deleting or renaming an image breaks every historical snapshot that still references it. Restored docs/images/crewai-otel-export.png from PR #3673; it was deleted in PR #4908 but v1.10.0 / v1.10.1 snapshots still reference it. Restoring instead of editing the snapshots preserves historical rendering fidelity and validates the new append-only rule retroactively. Tests: - lib/devtools/tests/test_docs_versioning.py covers the freeze: file copy, openapi rewrite, version insertion, default demotion, redirect upserts, per-section redirect rewriting, idempotency, and invalid inputs. Verified locally with mintlify broken-links: 0 broken links across the full site (Edge + 16 frozen versions, 4 locales). AGENTS.md (repo root) is the contributor guide for the new model; RELEASING.md is the release-cut runbook; README's Contribution section links to both. Co-authored-by: Cursor <cursoragent@cursor.com> * style: resolve linter issues --------- Co-authored-by: Cursor <cursoragent@cursor.com>
180 lines
5.0 KiB
Plaintext
180 lines
5.0 KiB
Plaintext
---
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title: "Enable Crew Studio"
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description: "Enabling Crew Studio on CrewAI AMP"
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icon: "comments"
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mode: "wide"
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---
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<Tip>
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Crew Studio is a powerful **no-code/low-code** tool that allows you to quickly
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scaffold or build Crews through a conversational interface.
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</Tip>
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## What is Crew Studio?
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Crew Studio is an innovative way to create AI agent crews without writing code.
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<Frame>
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</Frame>
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With Crew Studio, you can:
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- Chat with the Crew Assistant to describe your problem
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- Automatically generate agents and tasks
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- Select appropriate tools
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- Configure necessary inputs
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- Generate downloadable code for customization
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- Deploy directly to the CrewAI AMP platform
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## Configuration Steps
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Before you can start using Crew Studio, you need to configure your LLM connections:
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<Steps>
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<Step title="Set Up LLM Connection">
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Go to the **LLM Connections** tab in your CrewAI AMP dashboard and create a new LLM connection.
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<Note>
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Feel free to use any LLM provider you want that is supported by CrewAI.
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</Note>
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Configure your LLM connection:
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- Enter a `Connection Name` (e.g., `OpenAI`)
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- Select your model provider: `openai` or `azure`
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- Select models you'd like to use in your Studio-generated Crews
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- We recommend at least `gpt-4o`, `o1-mini`, and `gpt-4o-mini`
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- Add your API key as an environment variable:
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- For OpenAI: Add `OPENAI_API_KEY` with your API key
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- For Azure OpenAI: Refer to [this article](https://blog.crewai.com/configuring-azure-openai-with-crewai-a-comprehensive-guide/) for configuration details
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- Click `Add Connection` to save your configuration
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<Frame>
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</Frame>
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</Step>
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<Step title="Verify Connection Added">
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Once you complete the setup, you'll see your new connection added to the list of available connections.
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<Frame>
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</Frame>
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</Step>
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<Step title="Configure LLM Defaults">
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In the main menu, go to **Settings → Defaults** and configure the LLM Defaults settings:
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- Select default models for agents and other components
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- Set default configurations for Crew Studio
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Click `Save Settings` to apply your changes.
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<Frame>
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</Frame>
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</Step>
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</Steps>
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## Using Crew Studio
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Now that you've configured your LLM connection and default settings, you're ready to start using Crew Studio!
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<Steps>
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<Step title="Access Studio">
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Navigate to the **Studio** section in your CrewAI AMP dashboard.
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</Step>
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<Step title="Start a Conversation">
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Start a conversation with the Crew Assistant by describing the problem you want to solve:
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```md
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I need a crew that can research the latest AI developments and create a summary report.
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```
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The Crew Assistant will ask clarifying questions to better understand your requirements.
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</Step>
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<Step title="Review Generated Crew">
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Review the generated crew configuration, including:
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- Agents and their roles
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- Tasks to be performed
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- Required inputs
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- Tools to be used
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This is your opportunity to refine the configuration before proceeding.
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</Step>
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<Step title="Deploy or Download">
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Once you're satisfied with the configuration, you can:
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- Download the generated code for local customization
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- Deploy the crew directly to the CrewAI AMP platform
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- Modify the configuration and regenerate the crew
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</Step>
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<Step title="Test Your Crew">
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After deployment, test your crew with sample inputs to ensure it performs as expected.
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</Step>
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</Steps>
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<Tip>
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For best results, provide clear, detailed descriptions of what you want your
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crew to accomplish. Include specific inputs and expected outputs in your
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description.
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</Tip>
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## Example Workflow
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Here's a typical workflow for creating a crew with Crew Studio:
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<Steps>
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<Step title="Describe Your Problem">
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Start by describing your problem:
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```md
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I need a crew that can analyze financial news and provide investment recommendations
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```
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</Step>
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<Step title="Answer Questions">
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Respond to clarifying questions from the Crew Assistant to refine your
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requirements.
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</Step>
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<Step title="Review the Plan">
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Review the generated crew plan, which might include:
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- A Research Agent to gather financial news
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- An Analysis Agent to interpret the data
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- A Recommendations Agent to provide investment advice
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</Step>
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<Step title="Approve or Modify">
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Approve the plan or request changes if necessary.
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</Step>
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<Step title="Download or Deploy">
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Download the code for customization or deploy directly to the platform.
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</Step>
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<Step title="Test and Refine">
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Test your crew with sample inputs and refine as needed.
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</Step>
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</Steps>
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<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
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Contact our support team for assistance with Crew Studio or any other CrewAI
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AMP features.
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</Card>
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